python run_ner.py \
  --task_name=ner \
  --data_dir=./Data/NER_Data \
  --vocab_file=./ModelParams/chinese_L-12_H-768_A-12/vocab.txt \
  --bert_config_file=./ModelParams/chinese_L-12_H-768_A-12/bert_config.json \
  --output_dir=./Output/NER \
  --init_checkpoint=./ModelParams/chinese_L-12_H-768_A-12/bert_model.ckpt \
  --data_config_path=./Config/NER/ner_data.conf \
  --do_train=True \
  --do_eval=True \
  --max_seq_length=128 \
  --lstm_size=128 \
  --num_layers=1 \
  --train_batch_size=64 \
  --eval_batch_size=8 \
  --predict_batch_size=8 \
  --learning_rate=5e-5 \
  --num_train_epochs=1 \
  --droupout_rate=0.5 \
  --clip=5
